What marketers need to know about video deepfakes

If you've heard the term "deepfake," you might immediately be thinking of fraud, ethically questionable or downright disturbing videos that have been circulating around the internet over the last couple of years. As fake video content - and the AI technology that powers them - only get more sophisticated, it's imperative that both creators and marketers in every sector understand the ways they function and ways to use them to stay and keep ahead in our changing climate.

If you're not familiar with the term, deepfakes are synthetic media that has been altered digitally to substitute the appearance of a person convincingly, resulting in being able to make films which look and feel authentic yet they aren't. This is why it's normal that they may receive a negative rap for spreading misinformation or exploiting the likenesses of people.

As with any other technology it's in the way you use it. Creative and forward-thinking creators and marketers have been using deepfake technology and ethically in a responsible and ethical manner-to develop new forms of art, tell new stories, and improve their own video campaigns.

In this article we'll look at some instances of the use of fake technology to benefit society in addition to suggestions for how you can experiment with the tech yourself.

What is a deepfake?

A deepfake is a film, or audio recording, of someone whose facial or body is digitally changed. Deepfakes make use of AI to make likenesses, relying on pattern recognition to determine the expressions, tone, and movements.

The other terms used to describe a fake could refer to artificial or synthetic media, or artificially-generated content.

 An overview of deepfakes

The invention of the Generative Adversarial Networks (GAN) began the trend of real-looking fakes in 2014. GANs consist of two AI agents which make fakes and recognize forgery and allow the AI to develop over time.

The creation of Deepfakes is also possible by using a deep-learning computer network called a variational auto-encoder (VAE). VAEs are trained to encode pictures into low-dimensional representations of the object and decode the representations back into moving images.

The phrase "deepfake" was not coined until 2017 and, in the year media massed raised the alarm about fakes - with the first viral fake videos of Barack Obama and Donald Trump making the rounds across social media.

Deepfakes are also used for purposes that are becoming more and more useful to ordinary marketers and not only hackers or online trolls who try to spread false information.

What are the effects of deepfakes?

Machine learning AI is an essential part of developing a deepfake. Deepfakes rely on this technology to detect trends in images and data.

To create a fake deepfake video, an artist needs to provide these machine learning algorithms with hours of real footage, which then trains the deep neural network to detect patterns, tone faces, facial expressions and many more. The next step involves combining those learnings with graphics.

It's not difficult to make a fake, only existing audio or video of the person you want to replicate. And although it may appear difficult initially making a fake, it doesn't require complicated tools - the only requirement is basic knowledge in graphic design as well as video editing abilities.

Some examples of artistic video deepfakes

Marketers are in the early stages of adopting deepfakes and other AI technologies to help with video marketing and digital. These fake examples won't precisely fit into the marketer's toolbox just now However, they do demonstrate the capabilities of these AI technology right now.

 1. Chris Shimojima's "Dolche - Big Man"

This stunning Staff Picked music video from the filmmaker Chris Shimojima takes deepfake technology and flips it on its head, incorporating faces from 14 different performers (and 40 other contributions) to create a compelling story. The result is an artful and unexpected blend of technology and human expression.

 2. David Beckham's numerous languages

Malaria Needs to Die employed AI to influence soccer superstar David Beckham to speak in nine languages. They used fake technology to make an impact and markedly increase their campaigns' reach.

 3. Salvador Dali's museum greeting

It took over 1000 hours of machine-learning to enable the Dali museumMuseum to arrive at their fake version of Salvador Dali precisely perfect. The new technology gives visitors to museums an opportunity to see things from a different angle: they get to learn about the art of Salvador Dali from him himself!

Three everyday applications for deepfake technology for video

Though some uses of deepfakes are beyond an common marketer's grasp There are many innovative and interesting ways to use deepfake tech in your own job.

• Fix flubbed lines in the post If you have even cursory editing experience, you know the trials and tribulations of cutting together clean audio recordings from a informal interview. No matter if your client misspoke or didn't respond with a full phrase, using the technology of deepfake to fill in blanks can be a fantastic way to keep your post-production workflow moving along without the necessity of reshoots. (Just ensure you have the permission of your subject first obviously!)
   
  
• Personalize customer videos on a large the scale of Marketers are able to implement easy personalization by sending welcome or product videos that feature prospects' names or their company names. All you require is the names of your prospects and sufficient audio recorded from your camera for the deepfake technology to incorporate it into any video.
   
  
• Translate your video Deepfake technology introduces a brand new dimension of effortless translation. Instead of using subtitles, artificial intelligence is able to add spoken, translated audio or created using an audio bank or from the initial actor's voice.

New tech, new opportunities

We may not know exactly about what future developments in AI will provide However, there is one thing that's for certain: deepfakes will not go away. Similar to other AI-powered tech (chatGPT for instance? ) Anyone who is eager to try deepfakes while keeping their eyes open to the potential for pitfalls will be well-suited to compete in the changing world of video.